MX2007014330A

MX2007014330A - Adaptive customer assistance system for software products.

Info

Publication number: MX2007014330A
Application number: MX2007014330A
Authority: MX
Inventors: Hsiao-Wuen Hon; Sanjeev Katariya
Original assignee: Microsoft Corp
Priority date: 2005-05-20
Filing date: 2006-04-05
Publication date: 2008-02-12
Also published as: EP1883900A4; CN101180650A; WO2006127144A2; BRPI0610162A2; KR20080009130A; US20060265232A1; EP1883900A2; WO2006127144A3; JP2008541294A; RU2007142654A

Abstract

An adaptive customer assistance system that can serve as an integrated online and offline help platform for a suite of software products is provided. The assistance system includes a customer-interaction interface and a data management component and a download management component for distributed customer interaction. The data management component includes an authoring component, a download component, a runtime component and an analysis component. The runtime component, which includes a customer assistance model, is configured to receive a user-formulated question from the customer-interaction interface. The runtime component provides an answer to the user-formulated question based on information included in the customer assistance model. The analysis component automatically analyzes, in substantially real-time, the user-formulated question and the corresponding answer, and provides an analysis output for use in improving a quality of customer assistance.

Description

ADAPTABLE CUSTOMER AUXILIARY SYSTEM FOR SOFTWARE PRODUCTS BACKGROUND OF THE INVENTION The present invention in general refers to support facilities for software products. More particularly, the present invention relates to an adaptive client assistant system for software products. Most software products / applications are designed to include some type of help or auxiliary customer installation. These support facilities are usually designed in an integral way within the software application and, in general, they explain several components of the software application. Older help systems were only able to present the same information (or static information), without considering the context or circumstances surrounding the request for help. The most recent help systems provide context-sensitive help, which provides users with the specific help topic for the context to which it refers. For example, in a word processing application, if the user is editing a document and selects a command such as "FILE" from the drop-down menu and also presses a function key such as "F1" for HELP, a context-sensitive installation opens a window explaining the functions offered under the drop-down menu.

The help facilities described above clearly have several advantages over the search through printed documentation for help, which can be disruptive and time-consuming. In addition, context-specific help is relatively easy to use and provides information that focuses on a desired context. However, as mentioned before, these support facilities are usually designed within the software application and, therefore, may be inconsistent in appearance and content across multiple versions of the software application and may also be inconsistent with through multiple applications of a software site, for example. In addition, although some software applications allow a user to consult the installation of help using words, phrases and terminology of the natural language of the user, such systems have typically been unable to respond successfully to a sufficient number of questions that are useful to them. In addition, such systems do not include "learning" or self-tuning functions that allow the help system to automatically improve its assistance quality.

BRIEF DESCRIPTION OF THE INVENTION An adaptive client assistant system is provided that can serve as an integrated online and offline help platform for a set of software products. The system Auxiliary includes an interface for customer interaction and a data management component and a download management component for distributed customer interaction. The data management component includes an authorization component, a download component, a time-of-operation component and an analysis component. The operating time component, which includes an auxiliary customer model, is configured to receive a question asked by the user from the customer interaction interface. The operating time component provides an answer to the question asked by the user based on the information included in the auxiliary customer model. The analysis component automatically analyzes, substantially in real time, the question posed by the user and the corresponding response, and provides an analysis output to be used to improve a quality of customer support.

BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 is a block diagram of an illustrative computing environment in which the present invention can be implemented. Figure 2 is a block diagram of a software system using an adaptive client assistant system of the present invention. Figure 3 is a block diagram illustrating components of a modality of an adaptive client assistant system of the present invention. Figure 4 is a block diagram illustrating subcomponents of an operating time component of the adaptive client auxiliary system of Figure 3. Figure 5 is a block diagram illustrating subcomponents of an analysis component of the client assistant system adaptive of Figure 3. Figure 6 is a block diagram illustrating sub-components of a publishing component of the adaptive client helper system of Figure 3.

DETAILED DESCRIPTION OF THE ILLUSTRATIVE MODALITIES The present invention relates, in general, to a client assistant system for use with different software products. More specifically, the present invention provides an auxiliary customer system, which is self-inspecting and adaptable (uses a closed cycle action to optimize its operation) and can serve as a uniform or common support platform for different software products . However, before describing the present invention in greater detail, an illustrative embodiment wherein the present invention can be illustrated, should be discussed. Figure 1 illustrates an example of a system environment suitable computation 100 wherein the present invention can be implemented. The computing system environment 100 is only an example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the invention. Neither the computing environment 100 should be interpreted as having dependency or requirement in relation to any or a combination of components illustrated in the illustrative operating environment 100. The invention is operational with numerous other environments or configurations of general purpose or special purpose computing. Examples of well-known systems, environments and / or computer configurations that may be suitable for use with the invention include, but are not limited to, personal computers, server computers, portable devices, multiprocessor systems, microprocessor based systems, cable TV boxes, programmable consumer electronics, network PCs, minicomputers, macrocomputers, distributed computing environments that include any of the above systems or devices, and the like. The invention can be described in the general context of computer executable instructions, such as program modules, which are executed by a computer. In general, the program modules include routines, programs, objects, components, data structures, etc., which perform particular tasks or implement particular abstract data types. The The invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices ^ which are linked through a communications network. In a distributed computing environment, the program modules can be located in both local and remote computer storage media including memory storage devices. With reference to Figure 1, an illustrative system for implementing the invention includes a general-purpose computing device in the form of a computer 110. The components of the computer 110 may include, but are not limited to, a processing unit 120. , a system memory 130, and a common system conductor 121 that couples several system components, including the system memory, to the processing unit 120. The common system conductor 121 can be any of several types of memory structures. common driver including a common memory driver or memory controller, a common peripheral driver, and a local common conductor using any of a variety of common conductor architectures. By way of example, and not limitation, said architectures include a common driver of Standard Industry Architecture (ISA), common conductor of Micro Channel Architecture (MCA), enhanced ISA common conductor (EISA), local common conductor of Association of Video Electronics Standards (VESA), and common Peripheral Component Interconnect (PCl) driver also known as Mezanine's common driver. The computer 110 typically includes a variety of computer readable media. Computer-readable media can be any available means that can be accessed by the computer 110 that include both volatile and non-volatile media, removable and non-removable media. By way of example, and not limitation, computer readable media may comprise computer storage media and media. Computer storage media includes both volatile and non-volatile, removable and non-removable media, implemented in any method or technology for storing information such as computer-readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile discs (DVD), or other optical disk storage, magnetic cassettes, tape magnetic, magnetic disk storage or other magnetic storage devices, or any other means that can be used to store the desired information and which can be accessed by the computer 100. The media typically modalizes computer-readable instructions, data, program modules or other data in a modulated data signal such as a carrier WAV or other transport mechanism and includes any means of information provision. The term "modulated data signal" means a signal having one or more of its characteristics set or changed in such a way as to encode information in the signal. By way of example, and not limitation, the media includes means by cables such as a wired network or a direct cable connection, and wireless means such as acoustic, FR, infrared, and other wireless media. Combinations of any of the foregoing should also be included within the scope of computer readable media. The memory system 130 includes computer storage means in the form of a volatile and / or non-volatile memory such as read-only memory (ROM) 131 and random access memory (RAM) 132. An input / output system Basic 133 (BIOS), containing basic routines that help transfer information between elements within the computer 110, such as during startup, is typically stored in ROM 131. RAM 132 typically contains data and / or program modules that they are immediately accessible to and / or are actually operated by the processing unit 120. By way of example and not limitation, Figure 1 illustrates an operating system 134, application programs 135, other program modules 136, and program data 137. Computer 110 may also include other means of removable / non-removable, volatile / non-volatile computer storage. By way of example only, Figure 1 illustrates a hard disk drive 141 that reads from or writes to non-removable, non-volatile magnetic media, a magnetic disk unit 151 that reads or writes to a removable, non-volatile magnetic disk 152, and an optical disk drive 155 that reads or writes to a removable, non-volatile optical disk 156, such as a CD-ROM or other optical means. Other removable / non-removable, volatile / non-volatile computer storage media that can be used in the illustrative operating environment include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile discs, digital video cassette , Solid state RAM, solid state ROM, and the like. The hard disk drive 141 is typically connected to the common system bus 121 through a non-removable memory interface, such as the interface 140., and the magnetic disk unit 151 in the optical disk unit 155 are typically connected to the common system conductor 121 through a removable memory interface, such as the ipterfase 150. The units and their associated computer storage media discussed broadly illustrated in Figure 1 provide storage of computer-readable instructions, data structures, program modules and other data for computer 110. In Figure 1, for example, hard drive 141 is illustrated as storing the operating system 144, application programs 145, other program modules 146, and program data 147. Note that these components may be either the same or different from operating system 134, application programs 135, other program modules 136, and data of program 137. Operating system 144, application program 145, other program modules 146, and program data 147 are given different numbers here to illustrate that, at a minimum, they are different copies. A user can input commands and information to the computer 110 through input devices such as a keyboard 162, a microphone 163, and a pointing device 161, such as a mouse, trackball, or touch pad. Other input devices (not shown) may include a joystick, a game pad, a satellite antenna, a scanner, or the like. These and other input devices are usually connected to the processing unit 120 via a user input interface 160 which is coupled to the common system conductor, but can be connected by another common conductor structure and interface, such as a parallel port, a game port, or a common universal serial driver (USB). A monitor 191 or other type of display device is also connected to the common system driver 121 through an interface, such as a video interface 190. In addition to the monitor, computers may also include other peripheral output devices such as a speaker 197 and printer 196, which they can be connected through a peripheral output path 195. The computer 110 can operate in a networked environment using logical connections to one or more remote computers, such as a remote computer 180. The remote computer 180 can be a personal computer , a portable device, a server, a router, a network PC, an even device or other common network node, and typically includes many or all of the elements described above in relation to the computer 110. The logical connections illustrated in the Figure 1 includes a local area network (LAN) 171 and a wide area network (WAN) 173, but may also include other networks. Network environments are common places in offices, computer networks in companies, intranet and Internet.

When used in a LAN environment, the computer 110 connects to the LAN 171 through a network interface or adapter 170. When used in a WAN network environment, the computer 110 typically includes a 172 modem or others. means to establish communications through WAN 173, such as the Internet. The modem 172, which can be internal or external, can be connected to the common system conductor 121 through the user input interface 160, or other appropriate mechanism. In a networked environment, the program modules illustrated in relation to the computer 110, or portions thereof, may be stored in the remote memory storage device. By way of example and not limitation, Figure 1 illustrates programs of remote application 185 residing on the remote computer 180. It will be appreciated that the network connections shown are illustrative and other means may be used to establish a communications link between the computers. It should be noted that the present invention can be performed in a computer system such as that described with respect to Figure 1. However, the present invention can be performed on a server, a computer dedicated to handling messages, or on a distributed system wherein different portions of the present invention are made in different parts of the distributed computing system. Figure 2 is a simplified block diagram of a software system 200 that includes an adaptive client assistant system 202 of the present invention. The software system 200 includes a user interface 204, a set of software (a collection of software products, usually applications of related functionality, usually sharing a common user interface, more or less, and some ability to interchange data with each other in a moderate way) 206, and a component client auxiliary data handling 208. User interface 204 includes a software product interface component 210 and a client auxiliary interface component 212. For simplicity, FIG. 2 shows an individual separate communication path 214 of the component. from client auxiliary interface 212 to the management component of client auxiliary data 208. However, the client auxiliary data handling component 208 is typically accessible from different entry points or communication paths within components / products 216, 218 and 220 of the software set 206. As can be seen in Figure 2, the client auxiliary interface component 212 and the client auxiliary data management component 208 together form the client assistant system 202. In the embodiment shown in Figure 2, the client assistant system 202 serves as a common client auxiliary platform where components / products 216, 218 and 220 of the software set 206 may run. Such common client auxiliary platform helps to ensure that users experience consistent support through the components / products 216 , 218 and 220 of the software product 206. The client auxiliary system components 208 and 212 (or sub-components of these components) may reside in different parts of a distributed computing system. For example, in a client-server environment, the sub-components of the component 212, which are accessed by a client, reside in a client and the sub-components of the component 208 that store auxiliary client data may reside in a server . In said computing environment, a user writes a question (related to a certain application / component 216, 218, 220 of set 206, for example), and issues the question, after a client-user interface (sub-component of component 212). A server, (which includes at least some subcomponents of component 208) receives the question and provides a list of responses, which can be classified, for example. The user receives these responses in the client-user interface and typically presses (or selects) one or more of the responses to see details for a particular response, for example. The user can also classify (or re-classify) the responses. The system components 202, which are described in more detail below, can verify the questions entered by the user, the answer (s) is provided by the system 202 to the questions, the particular response (s) that the user selects from a list of classified answers, classifications assigned by a user to an answer, etc. The system 202 adds the feedback obtained by verifying the previous activities and uses the added feedback to substantially improve the real time, the importance of the answers and the general quality of help it provides to a user. In this way, the client assistant system 202 is an adaptive self-check system. It should be noted that customer help data (or help content) can be created using authorization tools, included in system 202, which are accessible from a user-server interface described below. Also, quality metrics are typically predefined in system 202 to help quantify the "quality of help" provided and then the "improvement gained" with the feedback. The adaptive self-checking nature of the system 202 will be more apparent from the following description of detailed embodiments of the present invention provided in conjunction with Figures 3 through 6. Figure 3 is a simplified block diagram illustrating components of an embodiment of the adaptive client auxiliary system 202 of the present invention. From the description provided above, it is clear that the client assistant system 202 is highly data-centric (or targeted) and essentially "handles" data and "presents" data. The general separation of data management functions / components from the data / component presentation functions (illustrated with the help of the faded line in Figure 3) helps to emphasize the nature driven by system data 202, and its components and subcomponents, emphasizing the limits of actions performed on the data as it progresses through the system 202. In Figure 3, the data presentation components include a customer auxiliary data creation interface. 212-1 (user interface for creating customer ancillary data using authorization tools) and a customer interaction interface 212-2 (presentation in the case of customer interaction). Shown between the presentation components 212-1 and 212-2 is the data management component 208 where, once created, the client auxiliary data (or content) is published, aggregated, transformed, delivered, collected and analyzed. .

In essence, the client assistant system 202 (shown in Figure 3) provides a substantially complete auxiliary user platform that has authorization tools that are employed to create the help content, publication systems that help to publish them, time systems of operation with which a user interacts to obtain search results of the published information, and feedback systems that aggregate the reworking in which the system also provides the aid Any question that of how it results in holes (gaps in content which result in that a user does not receive any information in response to a particular question) is identified by the system 202 and automatically communicated to the authorization environment that will be presented by an author The address / hole filling in this manner is a semi-automatic procedure However, as will be evident from the description of the sub-components of the system 202 provided below, the improvements in answers to questions, in general, occur automatically in the system 202 As mentioned above, the primary components of the system 202 of Figure 3 are the auxiliary data creation interface of the Client 212-1, Client Interaction Interface 212-2 and Data Management Component 208 Client Auxiliary Data Creation Interface (or User-Server Interface in a Client-Server Environment) 212-1 includes a content authorization workbench 302 and an authorization workbench 304. The content authorization workbench 302 includes authorization tools that contain authors that can be used to create help documents or files that are used to form an information repository for the system 202. An illustrative authorization tool that can be used to create the help documents is Microsoft® DOCStudio. Of course, you can also use others. The help documents that are produced from the content authorization workbench 302 may be Extensible Markup Language (XML) files connects corresponding data that includes document identification information, for example. The search authorization workbench 304 includes tools / modules that receive feedback from the data management component 208, without considering the importance of the responses provided, and provide feedback related to the added importance to the content authorization workbench. 302. The content authorization workbench 302 can use this feedback related to the aggregate importance to direct the authors to improve the content in the help files. The data handling component 208 includes a publishing component 306, an operating time component (or server operation time component in a client-server environment) 308 and an analysis component 310. The following is provided a brief description of the functions of each of these components, and a more detailed description of the sub-parts of the components 306, 308 and 310 in relation to Figures 4 to 6 is provided below. As can be seen in Figure 3, the component of publication 306 receives help files that are produced from the content authorization workbench 302. In general, the publication component 306 can receive help files from any source. In the publication component 306, the received help files introduce a "publication conduit" that coordinates the manner and sequence in which the help files are arranged and indexed. The main functions of the publishing component 306 include developing indexes and search catalogs that contain information from the authorized client auxiliary files. Indexes and search catalogs are jointly called models, which are produced by the publication component 306. Models may include Hypertext Markup Language (HTML) files and / or Microsoft Support Markup (MAML) files, or others. The operation time component 308 (or server operation time component in a client-server environment) receives models of the publication component 306 and stores the models to form an auxiliary information store of operation client, which may be accessed to provide answers to questions received from users through the interface of client-user 212-2. The server operation time component 308 typically responds to questions by providing a list of responses, which can be classified, for example. In one embodiment, the responses may be produced by the server operation time component 308 as HTML or MAML files. Also, the questions received through the customer-user interface 204-2, answers provided to the questions, the particular responses that the user selects from a list of classified answers, classifications assigned by a user to an answer, etc., are introduced by the server operation time component 308. In essence, when a user connects to the client assistant system 202 (or establishes a "session"), the server operation time system 308 may enter information during that time. session until the user disconnects from the system 202. In some embodiments, the operation time system 308 also handles operation related to user authorization, security and privacy of the client assistant system 202. The analysis component 310 uses information entered by the user. the server operation time component 308 to analyze and determine the quality of help provided by the system 2 02. The analysis component 310 adds the feedback introduced and uses the aggregate feedback to improve the importance of the answers and the general quality of help that the system 202 provides to a user. The analysis component 310 introduces information related to importance and quality to the search authorization workbench 304 and the publication component 308. In addition to its main subparts (publication component 306, operation time component 308 and analysis component 310), the data management component 208 may also include a published information download / update component (or a window update component in a windows environment) 312, which can provide current published information of the publication component 306 to a computer client. This feature allows a client computer to download a published client ancillary model and thus experience customer help even when it is disconnected (or offline) from the online client assistant system 202. A more detailed description of the subcomponents of the data handling component 308 are provided below in relation to Figures 4 to 6. As mentioned above, a user interacts with the client aid 202 through the client interaction interface (or client-client interface). user in a client-server environment) 212-2. The client-user interface 212-2 includes an operation time component (or client operation time component in a client-server environment) 314, which includes a search engine (not shown separately) and other sub-components (not shown), which can help verify the user activity (such as when the user presses through several routines when navigating through the results obtained from the server operation time component 308). Also, as mentioned above, a user can classify the responses provided by the system 202 and / or answer questions related to the specific quality specification owned by the system 202 through the customer-user interface 314. The questions asked by the user, classifications assigned by the user and other information related to the activity of the user is provided by the client operation time component 314 to the server operation time component 308. In some embodiments, the operation time component Client 314 can download client help models published through update component 312., although the client operation time component 314 has its own search engine, it can communicate with multiple search engines 316, and therefore, a user can use any of many search engines to interact with the client assistant system 202. Figure 4 is a block diagram illustrating subcomponents of the server operation time component 308 of the adaptive client helper system 202 of Figure 3. The server operation time component 308 includes a Web service component 402 , a data interface 404, a data processing component 406 and a storage of data 408. Web service component 402 is configured to receive "direct" Web service requests from a client and / or receive client responses through "gateways" such as Web sites. The component 402 arranges the information included in the received requests in a standard form for use by the data interface 404. The web service component 402 also outputs information in a form that is suitable for reception by the clients. Component 402 includes multiple "small" executable modules that typically do not have the full features and user interfaces of normal applications (sometimes referred to as small applications) that operate with each other to perform the previous "presentation" functions. The data interface 404 includes an input application program (API) interface 410, a query API 412, a query optimizer 414, a content retrieval API 416 and a content cache 418. The input API 410 is an interface through which the customer enters information, such as when the user clicks or clicks on entries and other user activity entered through the customer-user interface 212-2, is provided in a manner appropriate to an entry storage in the data storage 408, which will be described later. The query API 412 is an interface that receives questions asked by the user, through the Web service component 402, and provides the questions asked by the user in a manner suitable to the query optimizer 414. The query optimizer 414 arranges words and phrases in the question asked by the user in a configuration that is more manageable for faster execution by the downstream components. The content retrieval API 416 and the content cache 418 are included to provide relatively quick responses to frequently asked questions deriving the query construction components. The Content Recovery API 416 helps retrieve answers to frequently asked questions from the content cache 418, which stores frequently asked questions and corresponding responses. The data processing component 406 includes a question developer 420 and a search engine 422. The question developer 420 receives substantially "free text" questions from the question 414 optimizer and develops structured questions (such as structured SQL questions (Language Sequential Question)), which introduces them to the search engine 422. The search engine 422, generally includes any suitable module that is capable of executing the structured questions against the data storage component 408. The data storage 408 includes an input component 424 and a data storage model 426, which includes a learning model 428, a storage of free text property 430 and an index catalog 432. Input component 424 stores previously entered information mentioned, such as questions asked by the user, answers provided to the questions, responses that a user selects from a list of classified answers , classifications that a user assigns to a response, etc., and can provide the stored information to the analysis component 310. The model data storage 426 contains an operation time model provided by the publication component 306. As mentioned above The model data storage 426 includes a learning model 428, a free text property storage 430 and an index catalog 432. The learning model 428 includes responses, which the users classify as "good", and questions that correspond to those answers. The index catalog 432 includes indexes and search catalogs received from the publication component 306. The free text property storage 430 includes metadata for client auxiliary files. The search engine 422 runs against the components 428, 430 and 432 and, making comparisons with the information in the learning model 428, returns its substantially optimal responses to the user's questions through the data interface 404 and the Web service component 402. Figure 5 is a diagram of block illustrating sub-components of the analysis component 310 of the auxiliary system of adaptive client 202 of Figure 3. The analysis component 310 includes a data organization component 502, a data analysis component 504, a data unification component 506 and a business reporting component 508. The data component data organization 502 receives input data from the input storage 424 included in the server operation time component 308. The data entered into the input storage 424 is typically formatted by entering functions in a form that is optimized for input, but usually not adequate to perform the analysis. The data organization component 502 essentially extracts input current data from the input storage, transforms it into a scheme that is optimized for analysis, and stores the transformed data. The sub-components of the data organization component 502 include an extraction and transformation component 510, a cleaning and charging component 512, an authorization import component 514 and an elementary data store 516. The component 510 extracts data entered from the input storage 424 and, in accordance with a predetermined scheme that is optimized for analysis, separates explicit user feedback, implicit or extracted feedback, or other introduced information. The information extracted and transformed is provided to the cleaning and loading component 512, which performs heuristic data verification, data validation and, in some modalities, verification of unwanted publication. From this way, component 512 improves the data it receives and produces data in a way that is more suitable for analysis. The data extracted, transformed and cleaned are stored in the elementary data store 516, which is a data store that stores a certain scale of data (18 months, for example). The elementary data store 516 is normalized to reduce the size of the data storage and usually has maximum referential integrity. In order to provide better data for downstream analysis and reports, preferably document identification and authorization information (or metadata) were added to the extracted, transformed and clean data stored in the elementary data store 516. The importation of input 514 carries the import of metadata from publishing component 306 to the elementary data store 516. The data analysis component 504 has a primary purpose of analyzing data stored in the elementary data store 516, in order to improve the importance of the answers provided to an end user. The data analysis component 504 includes a number of sub-components that operate in conjunction with each other to perform the analysis of related importance. The subcomponents include a denormalizer 518, a controller storage 520, a denormalized elementary data store (DEWD) 522, a conduit controller 524, a processing component of importance 526, a user search link component 528, a session identification component 530, an integer processor 532, a regression fix identification (ID) component 534, a factor 536 generator, a relevance loader 538, a quality classification component 540 and a measurement component 542. As stated above, the schema of the elementary data warehouse is substantially normalized. The denormalizer 518 transforms the normalized data from the elementary data store 516 into a denormalized form and provides the denormalized data to the DEWD 522 for storage. The DEWD scheme is denormalized in order to support the requirements of downstream procedures. Since a large volume of data has to be denormalized, the denormalization of new data is done incrementally (in batches). The storage of the controller 520 includes intermittent logic that facilitates the denormalization of data in batches by the denormalizer 518. These are all processes within the denormalizer that are responsible for performing their own sub-analysis in a special way. In general, the conduit controller 522 handles the execution of processes in several sub-components of the data analysis component 504. For example, the conduit controller 522 determines the batches to be processed by different subcomponents of the analysis component of 504 data and after executes these processes in series to ensure that parent processes finish before they initiate processes that are dependent. The important processing component 526 is a classifier that groups corresponding questions and answers based on a predefined degree of importance. The user search join component 528 combines or "joins" questions that are formulated differently but are substantially similar in meaning and, therefore, can be satisfied by an individual / common response. The session identification component 530 includes logic that is capable of determining and grouping corresponding questions and answers based on different sessions that were established by the users in relation to the client assistant system 202. The identification component of regression fixation (ID ) 534 includes groups of test and logic data that help perform periodic tests on the importance classifier (processing component of importance 526) to determine if the classifier is improving over time with the ongoing addition of new training groups. classifier (or factors), which are generated and stored in the factor 536 generator. The importance 538 loader retrieves data from the DEWD 522, converts the data to a format that allows the efficient aggregation of this data, and provides the data to an important store in the data unification component 506. The classification component quality 540, in general, includes predefined metrics to quantify a quality of help provided by the system 202 Component 540 also includes logic to test quality classifications implicitly extracted against quality classifications assigned by the user, which helps to determine if certain models of analysis need to be altered Measurement component 542 is included to ensure that any replenishment that authors may wish to provide, is included in the analysis process. Authors' feedback is provided by measurement component 542 to the elementary data store 516, where this information, together with other processing information discussed above, it is stored. The data unification component 506 is a repository where different processed data is unified and stored in a form that is convenient to consume by consumers or customers of analysis. The unification component n data 506 includes an important warehouse 544 and a feedback warehouse The important warehouse 544 aggregates data it receives from the 538 importance shipper and also adds quality classifications that it receives from the quality classification component 540 This aggregate information is provided to the business reporting component 508 The 546 feedback storage stores any feedback that the authors wish to include in the analysis process. This feedback is received through the business reporting component 508 The 508 business reporting component includes software that can be used to design, generate and execute reports that can include information retrieved from the 544 importance store in different formats for analysis by authors, for example. In addition, component 508 may include programs that update the content of publication component 306 to thereby automatically improve the quality of the aid provided. Fig. 6 is a block diagram illustrating subcomponents of the publishing component 306 of the adaptive client auxiliary system 202 of Fig. 3. The publishing component 306 includes a conduit entry 602, a conduit processing component 604 and an output of conduit 606. Conduit entry 602 includes a work queue storage / placing component 608, a source determination store 610 and a production console 612. The storage / queue component 608 includes logic to receive questions, related to storage / queuing jobs, authorization tools (such as the content authorization workbench 302 (Figure 3)). Component 608 outputs records of job requests in operation and queued jobs that are ready to be dispatched. The source determination store 610 stores substantially all versions of help files that are received from the content authorization workbench 302. It also ensures that they are allocated.

Unique identifiers to all versions of the help files and metadata associated with these files. The production console 612 provides a user (customer production specialist, for example) with the ability to control a configuration of the storage / queuing component 608 and a conduit controller included in the conduit processing component 604 The conduit processing component 604 includes a conduit controller 614, an execution environment 616, which includes a development controller 618 and a rule machine 620, and a rule storage 622. The conduit controller 614 dispatches jobs queued to execution environment 616 and a delivery agent, which is part of conduit outlet 606. Load balancing is performed and can perform introduction and security functions. The development controller 618 governs the execution of jobs within an execution environment 616 and facilitates load balancing. The rule machine 620 applies rules to satisfy the work requirements by transforming or presenting source determinations (help files) to the determinations developed (indexes and search catalogs). Rule 622 storage is a common storage component of information and duct transformation configuration components (also known as "rules") that govern the transformation of source determinations to developed determinations.

The duct outlet 606 includes a developed determination storage 624 and a delivery agent 626. The developed determination storage 624 stores all the determinations produced (transformed, presented) (developed determinations) that are received from the execution environment 616. It also ensures that unique identifiers are assigned to all determinations or files developed, and associated metadata developed with these files. The delivery agent 626 includes logic performing a synchronized step transfer of developed determinations to the server operation time component 308. The developed determinations are also provided to the download component 312, from which a client computer may download information from the client. help. It should be noted that the components and subcomponents of the client assistant system 202 are designed in a way that allows the separate development of the individual components and subsequent connection of these components to form the system 202. In other words, the system 202 is designed as a "workable" work structure. The client assistant system 202 of the present invention is essential and directly connects a user of an application to the application and to the developer of the application. The continuous feedback mechanism helps to ensure that the more a user interacts with the client assistant system 202, the better it will work.

In summary, the provision of customer assistance in accordance with the embodiments of the present invention involves creating help content, publishing help files to online servers, and preparing help files that will be downloaded to clients' machines. Client machines, when connected, interact with their online servers. Through this interaction, feedback is gathered and used to improve the relevance or importance of user interaction, thus impacting both the search and navigation and helping to build better help documentation. Through feedback, new models of relevance and content mode are generated. New models and content are then made available to online systems, and client download systems, through the publishing system. This cycle is continuous and, therefore, customer support is improved over time. Although the present invention has been described with reference to particular embodiments, those skilled in the art will recognize that changes can be made in form and detail without departing from the spirit and scope of the invention.

Claims

CLAIMS 1. An auxiliary client system comprising: a customer interaction interface; and a data management component comprising: an operating time component, which includes an auxiliary client model, configured to receive a question asked by a user from the customer interaction interface, and to provide a response to the question asked by the user, based on the information included in the auxiliary customer model, through the customer interaction interface; and an analysis component configured to automatically analyze the question asked by the user and the corresponding response, and to provide an analysis output to be used in the improvement of a quality of customer support. The client assistant system according to claim 1, wherein the data management component further comprises a publishing component that is configured to receive authorized client help files and to form an auxiliary client model based on the authorized client help files received, and wherein the publishing component is further configured to provide the auxiliary client model to the operation time component. 3. The client assistant system according to claim 2, wherein the auxiliary client model comprises Indexes and search catalogs that include information from the authorized client auxiliary files. 4. The client assistant system according to claim 2, further comprising a client data creation interface for updating the auxiliary client files. 5. The client assistant system according to claim 1, wherein the operating time component comprises an input component that stores the question asked by the user, the corresponding response and the information related to a degree of user satisfaction with the user. answer. 6. The client assistant system according to claim 5, wherein the analysis component performs the automatic analysis retrieving, from the input component, the question asked by the user, the corresponding response and the information related to a degree of satisfaction of the user and analyze the question formulated by the user recovered, the response and the information related to the degree of user satisfaction with the response. 7. The client assistant system according to claim 1, wherein the analysis output is based on a quality classification assigned by the user for the response provided by the question posed by the user. 8. The client assistant system according to claim 1, wherein the analysis output is based on a quality classification implicitly extracted for the answer provided by the question asked by the user. 9. The client assistant system according to claim 1, wherein the analysis output is based on a quality classification assigned by the user, and an implicitly extracted quality classification, for the response provided for the question asked by the user. user. The client assistant system according to claim 1, wherein the analysis output is used by the publishing component to update the client auxiliary model. The client assistant system according to claim 2, wherein the analysis output is used by authors as a guiding line to create new auxiliary client files. The client assistant system according to claim 1, wherein the analysis component is further configured to detect holes that define missing customer auxiliary information. 13. A computer-implemented software system employing the auxiliary client system of claim 1 as a common client assistant platform for a group of software products. The client assistant system according to claim 1, wherein the analysis component is configured to automatically analyze, substantially in real time, the question asked by the user and the corresponding response. 15. A method implemented by computer to provide customer support for software products, comprising: receiving a question asked by the user; provide, based on the information included in an auxiliary customer model, a response to the question asked by the user; analyze, substantially in real time, the question asked by the user and the corresponding response; and provide an analytical output to be used in quality improvement of customer support. 16. The method according to claim 15, further comprising forming an auxiliary nt model from authorized nt auxiliary files. The method according to claim 16, wherein the nt auxiliary model comprises indexes and search catalogs containing information from the authorized nt auxiliary files. 18. The method according to claim 15, wherein the analysis output is based on a quality classification assigned by the user for the response provided for the question asked by the user. 19. The method according to claim 15, wherein The analysis output is based on an implicitly extracted quality classification for the response provided for the question asked by the user. 20. The method according to claim 15, wherein the analysis output is used to update the nt auxiliary model.